ET and SPECT imaging at Massachusetts General Hospital is actively supported by NIH- funded research and addresses questions of fundamental importance in the fields of neurology, oncology, cardiology, neuroscience, tumor biology and molecular imaging. There are several significant advances in nuclear medicine imaging, such as dynamic imaging for kinetic modeling of novel PET radiopharmaceuticals, PET-MR, time-of-flight PET, and quantitative SPECT-CT, that have triggered active research in modeling, simulation and image reconstruction for these new applications. Image reconstruction using additional dimensions from energy, time-of-flight, and dynamic time frame requires unprecedented computer memory and speed to model extremely large system matrices. A supercomputer with a very large shared memory is critical for such applications because using distributed memory across a standard computer cluster, which consists of multiple nodes connected by network, is severely limited by the slow node-to-node network connections. We propose a Silicon Graphics Inc. Altix UV 1000 global shared memory supercomputer with 2 TB memory and 256 Intel Xeon cores. This system will serve a large group of funded NIH investigators and will yield substantial improvement in the quality of their research by enhancing image quality and accuracy in quantitative PET and biomedical imaging.